• Energy Research
• Open Access close
• CN close
• IN close
• BE close

Different species within the same community may exhibit distinct phenological responses to climate change, so it is necessary to study species differences in the green-up date among abundant species within a wide area, and a suitable phenology model should be introduced to explain the associated climate-driven mechanism. Although various models have been developed, very few studies have aimed to compare their efficiency and robustness, and the relative contributions of climate driving factors have not been sufficiently examined. We analyzed phenology data for 12 species across 17 stations in Inner Mongolia and found that essential spatiotemporal and interspecies differences existed in the green-up date. Five process-based models were established for each species and their performance was comprehensively evaluated. The two-phase models (sequential model, parallel model, unified model and unified model combined with precipitation driving) generally performed better than the one-phase model (thermal time model), and the model considering precipitation performed the best, which indicates that it is necessary to introduce the chilling effect and precipitation driving effect to improve the model accuracy in arid environments. We proposed a method to estimate the contribution rates of various climate driving factors, and significant differences in the relative demand for the various climate driving factors among different species were clearly revealed. The results indicated that for natural vegetation in Inner Mongolia, the need for the chilling and temperature driving is relatively high, and the precipitation driving is very important for herbaceous vegetation, which leads to considerable spatial and interspecies differences in green-up date. We demonstrated the feasibility of quantitatively evaluating the contributions of different climate driving factors with a process-based model, and the contradiction in phenological changes among different studies may eventually be clarified.

The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

To study the heating performance of a solar-assisted cold-water phase-change-energy heat pump system, its heating performance under series and parallel connections is simulated for a community in Harbin, the influence of ice thickness on the different operation modes is analyzed, and the economy of the system is calculated for series and parallel connections in this paper. The results show that the water supply temperature is higher and more uniform in the parallel operation, and more terminal heat is supplied; the ice thickness has more of an influence on the series connection compared to the parallel connection; and the dynamic payback period is 6.72 years for the series connection and 7.28 years for the parallel connection. This case study can serve as a guide for practical engineering application projects and act as a reference for heating and economic data for the promotion of this heat pump system.

In recent years, food security, especially supply, has been an important issue in China’s agricultural production. The stability of grain prices is related to the stability and development of the grain market. Based on agricultural production data from 1970 to 2015, this paper explores the influence of agricultural product price fluctuation on grain production by using the cobweb theory and vector error correction (VEC) model. The results show that changes in grain production in China are affected by fluctuations in agricultural product prices, that the production change lags behind the price change, and that there is a long-term equilibrium relationship between grain yield and agricultural product price. A Granger causality test shows that the change in agricultural product price is the Granger cause of grain yield change.

Symbiodiniaceae species is a dinoflagellate that plays a crucial role in maintaining the symbiotic mutualism of reef-building corals in the ocean. Reef-building corals, as hosts, provide the nutrition and habitat to endosymbiotic Symbiodiniaceae species and Symbiodiniaceae species transfer the fixed carbon to the corals for growth. Environmental stress is one of the factors impacting the physiology and metabolism of the corals-dinoflagellate association. The environmental stress triggers the metabolic changes in Symbiodiniaceae species resulting in an increase in the production of survival organelles related to storage components such as lipid droplets (LD). LDs are found as unique organelles, mainly composed of triacylglycerols surrounded by phospholipids embedded with some proteins. To date, it has been reported that investigation of lipid droplets significantly present in animals and plants led to the understanding that lipid droplets play a key role in lipid storage and transport. The major challenge of investigating endosymbiotic Symbiodiniaceae species lies in overcoming the strategies in isolating lesser lipid droplets present in its intercellular cells. Here, we review the most recent highlights of LD research in endosymbiotic Symbiodiniaceae species particularly focusing on LD biogenesis, mechanism, and major lipid droplet proteins. Moreover, to comprehend potential novel ways of energy storage in the symbiotic interaction between endosymbiotic Symbiodiniaceae species and its host, we also emphasize recent emerging environmental factors such as temperature, ocean acidification, and nutrient impacting the accumulation of lipid droplets in endosymbiotic Symbiodiniaceae species.

In response to the pressing need for transportation decarbonization, this paper examines the often overlooked domain of inland waterway transport and seeks to answer which alternative fuel or power source is the most promising for that sector. As the shipping industry significantly contributes to global carbon emissions, it has been shifting towards alternative fuels and decarbonization measures in the effort to reduce them, whereas the inland waterways, operating predominantly on diesel engines, have not achieved equivalent substantial progress. Employing a systematic literature review and regional analysis, this study identifies notable trends. LNG initially emerged as a favored alternative fuel, but recent studies emphasize a shift towards “greener” solutions like batteries and hydrogen. Europe and Asia lead in these developments. This investigation uncovers critical gaps in research and development, particularly in the Northern European countries that have extensive inland waterway networks. It also calls for future studies to explore the performance of vessels that have adopted LNG compared to other emerging alternatives and emphasizes the importance of considering the time lag between technology development and research publication.

Using wind energy in the natural environment provides a promising solution for wireless sensor power supply for ecological, meteorological, environmental, and infrastructure monitoring. However, the uncertainty and disorder of natural wind restrict the further development of wind energy harvester systems and self-powered wireless sensor technology. Hence, this paper proposes a self-regulation blade wind energy harvester system (SBWEHS) for self-powered wireless monitoring sensors in remote field areas with power shortages. The system is mainly composed of three parts: wind harvesting mechanism, generator module, and energy storage module. The device can control the blade overlap ratio according to the wind speed while generating electricity to maximize the power coefficient. The system can control the blade’s closure in bad weather to protect the device. Based on the computational fluid dynamics technology of Ansys Fluent software, this study evaluated the impact of wind speed and blade overlap ratio on the two-stage blades. Experiments revealed that when the overlap ratio of the blades is fixed at 0.2 and the wind speed is set at 16 m/s, the maximum average power will reach 0.79 W, which fulfills the power requirements of wireless sensors. These results illustrate that the SBWEHS can effectively supply power for wireless monitoring sensors, especially in remote natural environments.

Aiming at the large carbon emissions of facility agricultural heating in severe cold regions in winter, a compound parabolic concentrator based soil heating system was presented. The system integrated with novel trough compound parabolic concentrator and was used for soil heating in facility agriculture. Following the structure of the compound parabolic concentrator, TracePro software was selected to trace the light in the compound parabolic concentrator. The variation trend of the light escape rate of the compound parabolic concentrator with the different incident angles was analyzed. Based on the calculation results, the performance of the solar collector system was investigated, and the impact of circulating air velocity on the photo-thermal performance of the solar collector system was explored. Research results indicate that when the circulating air velocity is 1.4 m/s and the average ambient temperature is about 28.9?, the temperature of the system outlet is up to 90.9?. The average instantaneous heat collection, maximum photo-thermal conversion efficiency, and unit area heat collection of the system are 740.6 W, 27.83%, and 0.8 MJ/m2, respectively. This research can effectively promote the efficient integration of the solar collector system in facility agriculture.